1. Integration of an absorption chiller to a process applying the pinch analysis approachAndreja Nemet, Zdravko Kravanja, Miloš Bogataj, 2022, izvirni znanstveni članek Opis: In addition to the consumption of hot utilities, there is also a significant cost associated
with the consumption of cold utilities when there is a high demand for cooling. A promising
solution for cooling is an absorption chiller (AC), which uses heat instead of electricity for cooling.
A thermodynamic approach for evaluating AC integrated with a process is presented in this work.
A model for assessing the properties and duties of an AC cycle was developed. The integration of
a combined process-AC system was evaluated using the Grand Composite Curve. Three different
options of integration were analyzed: (i) above the Pinch, (ii) below the Pinch, and (iii) across the
Pinch. AC represents the combined effect of a heat engine and a heat pump, as the generator together
with the absorber and condenser has the function of a heat engine, while the evaporator combined
with the absorber and condenser mimics the function of a heat pump. The comparison between the
non-integrated and integrated process-AC systems has revealed that the proper placement of AC is
across or below the Pinch and the improper is above the Pinch. If AC was entirely integrated below
the Pinch, the integration would result in a complete (100%) reduction in the consumption of hot
utility for the operation of AC. The most suitable placement of AC with double reduction of hot
utility consumption and complete reduction of both hot and cold utility to operate AC is across the
Pinch due to the pumping of heat through AC from below to above the Pinch.
Ključne besede: absorption chiller, Pinch analysis, heat integration, low-temperature heat
Objavljeno v DKUM: 15.05.2025; Ogledov: 0; Prenosov: 0
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2. Improving personalized meal planning with large language models: identifying and decomposing compound ingredientsLeon Kopitar, Leon Bedrač, Larissa Jane Strath, Jiang Bian, Gregor Štiglic, 2025, izvirni znanstveni članek Opis: Background/Objectives: Identifying and decomposing compound ingredients within meal plans presents meal customization and nutritional analysis challenges. It is essential for accurately identifying and replacing problematic ingredients linked to allergies or intolerances and helping nutritional evaluation. Methods: This study explored the effectiveness of three large language models (LLMs)—GPT-4o, Llama-3 (70B), and Mixtral (8x7B), in decomposing compound ingredients into basic ingredients within meal plans. GPT-4o was used to generate 15 structured meal plans, each containing compound ingredients. Each LLM then identified and decomposed these compound items into basic ingredients. The decomposed ingredients were matched to entries in a subset of the USDA FoodData Central repository using API-based search and mapping techniques. Nutritional values were retrieved and aggregated to evaluate accuracy of decomposition. Performance was assessed through manual review by nutritionists and quantified using accuracy and F1-score. Statistical significance was tested using paired t-tests or Wilcoxon signed-rank tests based on normality. Results: Results showed that large models—both Llama-3 (70B) and GPT-4o—outperformed Mixtral (8x7B), achieving average F1-scores of 0.894 (95% CI: 0.84–0.95) and 0.842 (95% CI: 0.79–0.89), respectively, compared to an F1-score of 0.690 (95% CI: 0.62–0.76) from Mixtral (8x7B). Conclusions: The open-source Llama-3 (70B) model achieved the best performance, outperforming the commercial GPT-4o model, showing its superior ability to consistently break down compound ingredients into precise quantities within meal plans and illustrating its potential to enhance meal customization and nutritional analysis. These findings underscore the potential role of advanced LLMs in precision nutrition and their application in promoting healthier dietary practices tailored to individual preferences and needs.
Ključne besede: artificial intelligence, food analysis, LLM, Ilama, GPT, mixtral, ingredient identification, ingredient decomposition, personalized nutrition, meal customization, nutritional analysis, dietary planning
Objavljeno v DKUM: 08.05.2025; Ogledov: 0; Prenosov: 1
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3. Thermogravimetric, kinetic and thermodynamic behaviour of raw and hydrothermally pretreated oil cakes during pyrolysis and TG-FTIR analysis of the gaseous productsAleksandra Petrovič, Sabina Vohl, Sven Gruber, Klemen Rola, Tjaša Cenčič, Lidija Čuček, Danijela Urbancl, 2025, izvirni znanstveni članek Opis: The pyrolysis of raw and hydrothermally (HTC) pretreated pumpkin (PC) and hemp (HC) oilseed cakes was investigated for the first time using thermogravimetric, kinetic and thermodynamic analyses. The influence of the HTC pretreatment and the type of reaction liquid (whey or water) on the pyrolysis was investigated and the pyrolysis gases were analysed. The HTC pretreatment increases the biochar yield with values of up to 44 wt.% compared to raw oil cakes (∼27 wt.%). The HTC pretreatment with whey resulted in a higher energy and biochar yield and better biochar properties than the pretreatment with water. The tested oil cakes provided comparable energy yields, although HC provided higher biochar yields, while PC biochar showed higher hydrophobicity. The kinetic modelling shows that the activation energies () for the pyrolysis of the raw oil cakes varied between 93.6 and 529.9 kJ/mol for PC and between 71.3 and 669.9 kJ/mol for the HC sample. HTC pretreatment in water media increased the values, while the use of whey led to a decrease in the values. TG-FTIR analysis of the emitted gases showed that the HTC treatment affected the release of CO2 and hydrocarbons as well as the pyrolysis mechanism and reaction pathways
Ključne besede: oilseed cake, hydrochar, pyrolysis, thermogravimetric analysis, kinetic analysis, gas emissions
Objavljeno v DKUM: 25.04.2025; Ogledov: 0; Prenosov: 6
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4. Investment plan and evaluation of the transition of a farm to a wellness tourist farmTatjana Klakočar, Karmen Pažek, Lazar Pavić, 2023, izvirni znanstveni članek Opis: This study aimed to develop a commercial concept for transforming farms into wellness tourist destinations. The proposed scenario involved the renovation of a hayrack into a highend tourist accommodation, comprising relaxation rooms with panoramic glass walls and the renovation of the barns, as well as an outdoor swimming pond. The research methods included
description, compilation, and synthesis to explore the legislation in Slovenia related to investment performance and trends in wellness tourism to support the realisation of the proposed investment. Furthermore, the study used the method of financial estimation of investment using cost-benefit analysis to facilitate the transition. Four datasets were used for the estimation: investment income, investment costs, end value of the investment, and annual interest rate. The estimated investment cost was €530,000 and the total estimated revenue was €192,720, with total costs amounting to 50% of the total income, as well as an annual cash flow of €96,360, which was used in the assessment of the investment return period. According to the findings, the investment return period is 15 years with the lowest annual cash flow and interest rate of 3.5%. However, caution is advised due to uncertainties in the long-term costs of raw materials and energy.
Ključne besede: tourist farm, wellness, cost-benefit analysis
Objavljeno v DKUM: 23.04.2025; Ogledov: 0; Prenosov: 0
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6. EEG-based finger movement classification with intrinsic time-scale decompositionMurside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Yalcin Isler, 2024, izvirni znanstveni članek Ključne besede: brain-computer interfaces, electroencephalogram, feature reduction, machine learning, finger movements classification, time series analysis
Objavljeno v DKUM: 16.04.2025; Ogledov: 0; Prenosov: 0
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7. Optimizing digital image quality for improved skin cancer detectionBogdan Dugonik, Marjan Golob, Marko Marhl, Aleksandra Vučinič Dugonik, 2025, izvirni znanstveni članek Opis: The rising incidence of skin cancer, particularly melanoma, underscores the need for improved diagnostic tools in dermatology. Accurate imaging plays a crucial role in early detection, yet challenges related to color accuracy, image distortion, and resolution persist, leading to diagnostic errors. This study addresses these issues by evaluating color reproduction accuracy across various imaging devices and lighting conditions. Using a ColorChecker test chart, color deviations were measured through Euclidean distances (∆E*, ∆C*), and nonlinear color differences (∆E00, ∆C00), while the color rendering index (CRI) and television lighting consistency index (TLCI) were used to evaluate the influence of light sources on image accuracy. Significant color discrepancies were identified among mobile phones, DSLRs, and mirrorless cameras, with inadequate dermatoscope lighting systems contributing to further inaccuracies. We demonstrate practical applications, including manual camera adjustments, grayscale reference cards, post-processing techniques, and optimized lighting conditions, to improve color accuracy. This study provides applicable solutions for enhancing color accuracy in dermatological imaging, emphasizing the need for standardized calibration techniques and imaging protocols to improve diagnostic reliability, support AI-assisted skin cancer detection, and contribute to high-quality image databases for clinical and automated analysis.
Ključne besede: dermoscopy, melanoma, color analysis, color error, spectral power distribution, grey card, digital imaging standards
Objavljeno v DKUM: 08.04.2025; Ogledov: 0; Prenosov: 3
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8. Parkinson’s disease non-motor subtypes classification in a group of Slovenian patients : actuarial vs. data-driven approachTimotej Petrijan, Jan Zmazek, Marija Menih, 2023, izvirni znanstveni članek Opis: Background and purpose: The aim of this study was to examine the risk factors, prodromal symptoms, non-motor symptoms (NMS), and motor symptoms (MS) in different Parkinson’s disease (PD) non-motor subtypes, classified using newly established criteria and a data-driven approach.
Methods: A total of 168 patients with idiopathic PD underwent comprehensive NMS and MS examinations. NMS were assessed by the Non-Motor Symptom Scale (NMSS), Montreal Cognitive Assessment (MoCA), Hamilton Depression Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Epworth Sleepiness Scale (ESS), Starkstein Apathy Scale (SAS) and Fatigue Severity Scale (FSS). Motor subtypes were classified based on Stebbins’ method. Patients were classified into groups of three NMS subtypes (cortical, limbic, and brainstem) based on the newly designed inclusion criteria. Further, data-driven clustering was performed as an alternative, statistical learning-based classification approach. The two classification approaches were compared for consistency.
Results: We identified 38 (22.6%) patients with the cortical subtype, 48 (28.6%) with the limbic, and 82 (48.8%) patients with the brainstem NMS PD subtype. Using a data-driven approach, we identified five different clusters. Three corresponded to the cortical, limbic, and brainstem subtypes, while the two additional clusters may have represented patients with early and advanced PD. Pearson chi-square test of independence revealed that a priori classification and cluster membership were significantly related to one another with a large effect size (χ2(8) = 175.001, p < 0.001, Cramer’s V = 0.722). The demographic and clinical profiles differed between NMS subtypes and clusters.
Conclusion: Using the actuarial and clustering approach, marked differences between individual NMS subtypes were found. The newly established criteria have potential as a simplified tool for future clinical research of NMS subtypes of Parkinson’s disease.
Ključne besede: Parkinson’s disease, non-motor symptoms subtypes, a priori classification, cluster analysis
Objavljeno v DKUM: 07.04.2025; Ogledov: 0; Prenosov: 2
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9. Integrating live cell calcium imaging and tissue damage assessment in a novel model of acute pancreatitisPolona Kovačič, Maša Skelin, Eva Paradiž, Viktória Venglovecz, Loránd Kiss, Gabriella Mihalekné Fűr, Andraž Stožer, Jurij Dolenšek, 2025, objavljeni povzetek znanstvenega prispevka na konferenci Ključne besede: acute pancreatitis, calcium imaging, LiveDead assay, pancreatic tissue slices, histological analysis
Objavljeno v DKUM: 31.03.2025; Ogledov: 0; Prenosov: 13
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10. STALITA: innovative platform for bank transactions analysisDavid Jesenko, Štefan Kohek, Borut Žalik, Matej Brumen, Domen Kavran, Niko Lukač, Andrej Živec, Aleksander Pur, 2022, izvirni znanstveni članek Opis: Acts of fraud have become much more prevalent in the financial industry with the rise
of technology and the continued economic growth in modern society. Fraudsters are evolving
their approaches continuously to exploit the vulnerabilities of the current prevention measures
in place, many of whom are targeting the financial sector. To overcome and investigate financial
frauds, this paper presents STALITA, which is an innovative platform for the analysis of bank
transactions. STALITA enables graph-based data analysis using a powerful Neo4j graph database
and the Cypher query language. Additionally, a diversity of other supporting tools, such as support
for heterogeneous data sources, force-based graph visualisation, pivot tables, and time charts, enable
in-depth investigation of the available data. In the Results section, we present the usability of the
platform through real-world case scenarios.
Ključne besede: Neo4j, platform, bank transactions, graph analysis, graph visualisation, fraud, investigation
Objavljeno v DKUM: 27.03.2025; Ogledov: 0; Prenosov: 2
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